Coding and Common Reconstruction

This work studies problems of source and joint source-channel coding under the requirement that the encoder can produce an exact copy of the compressed source constructed by the decoder. This requirement, termed here as the common reconstruction constraint (CR) , is satisfied automatically in rate-d...

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Published in:IEEE transactions on information theory Vol. 55; no. 11; pp. 4995 - 5010
Main Author: Steinberg, Y.
Format: Journal Article
Language:English
Published: New York, NY IEEE 01.11.2009
Institute of Electrical and Electronics Engineers
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
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ISSN:0018-9448, 1557-9654
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Abstract This work studies problems of source and joint source-channel coding under the requirement that the encoder can produce an exact copy of the compressed source constructed by the decoder. This requirement, termed here as the common reconstruction constraint (CR) , is satisfied automatically in rate-distortion theory for single sources. However, in the common formulation of problems of lossy source coding with side information at the decoder (the Wyner-Ziv problem), distributed source coding, and joint source-channel coding for networks, the destination can exploit the information it receives in a manner that cannot be exactly reproduced at the sender side. Some applications, like the transmission of sensitive medical information, may require that both sides-the sender and the receiver-will share a common version of the compressed data, for the purpose of future discussions or consulting. The purpose of this work is to study the implications of CR constraints on the achievable rates in scenarios of lossy source coding and lossy transmission of sources. Three problems are examined: source coding with side information at the decoder, simultaneous transmission of data and state over state-dependent channels, and joint source-channel coding for the degraded broadcast channel. Single-letter characterizations of the optimal performance are developed for these problems, under corresponding CR constraints. Implications of this constraint on problems of joint source-channel coding in networks are discussed.
AbstractList This work studies problems of source and joint source-channel coding under the requirement that the encoder can produce an exact copy of the compressed source constructed by the decoder. This requirement, termed here as the common reconstruction constraint (CR) , is satisfied automatically in rate-distortion theory for single sources. However, in the common formulation of problems of lossy source coding with side information at the decoder (the Wyner-Ziv problem), distributed source coding, and joint source-channel coding for networks, the destination can exploit the information it receives in a manner that cannot be exactly reproduced at the sender side. Some applications, like the transmission of sensitive medical information, may require that both sides-the sender and the receiver-will share a common version of the compressed data, for the purpose of future discussions or consulting. The purpose of this work is to study the implications of CR constraints on the achievable rates in scenarios of lossy source coding and lossy transmission of sources. Three problems are examined: source coding with side information at the decoder, simultaneous transmission of data and state over state-dependent channels, and joint source-channel coding for the degraded broadcast channel. Single-letter characterizations of the optimal performance are developed for these problems, under corresponding CR constraints. Implications of this constraint on problems of joint source-channel coding in networks are discussed.
This work studies problems of source and joint source-channel coding under the requirement that the encoder can produce an exact copy of the compressed source constructed by the decoder. This requirement, termed here as the common reconstruction constraint (CR), is satisfied automatically in rate-distortion theory for single sources. However, in the common formulation of problems of lossy source coding with side information at the decoder (the Wyner-Ziv problem), distributed source coding, and joint source-channel coding for networks, the destination can exploit the information it receives in a manner that cannot be exactly reproduced at the sender side. Some applications, like the transmission of sensitive medical information, may require that both sides - the sender and the receiver - will share a common version of the compressed data, for the purpose of future discussions or consulting. The purpose of this work is to study the implications of CR constraints on the achievable rates in scenarios of lossy source coding and lossy transmission of sources. Three problems are examined: source coding with side information at the decoder, simultaneous transmission of data and state over state-dependent channels, and joint source-channel coding for the degraded broadcast channel. Single-letter characterizations of the optimal performance are developed for these problems, under corresponding CR constraints. Implications of this constraint on problems of joint source-channel coding in networks are discussed. [PUBLICATION ABSTRACT]
Author Steinberg, Y.
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Issue 11
Keywords Performance evaluation
joint source-channel coding
Broadcast channel
Source coding
successive refinement
Refinement method
common reconstruction (CR)
Distributed source signal
Rate distortion theory
Lossy medium
hierarchical coding
Decoding
state-dependent channels
Joint source channel coding
Gel'fand―Pinsker channel
Broadcast channels
Wyner-Ziv problem
Wyner Ziv problem
source coding with side information
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SubjectTerms Applied sciences
Broadcast channel
Broadcasting
Channel coding
Channels
Chromium
Codes
Coding
Coding, codes
common reconstruction (CR)
Communication channels
Compressed
Constraint theory
Data transmission
Decoders
Decoding
Degradation
Exact sciences and technology
Gel'fand-Pinsker channel
hierarchical coding
Information theory
Information, signal and communications theory
joint source- channel coding
Networks
Performance loss
Propagation losses
Reconstruction
Reproduction
Signal and communications theory
Source coding
source coding with side information
state-dependent channels
Studies
successive refinement
Telecommunications and information theory
Wyner-Ziv problem
Title Coding and Common Reconstruction
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